My research interest is aimed towards the understanding of the 'dynamics' of soft matter systems, within the "classical statistical mechanics" framework. Particular focus is on the non-equilibrium dynamics of fluids, close to a second-order phase transition. Few topics that I work on: (a) optically heated active colloids, (b) confined near-critical fluids and surface effects, (c) Casimir forces, (d) collective dynamics in fluids, (e) droplet coalescence, (f) phase separation, and aging, etc. For this purpose, I exploit a variety of computational techniques such as GPU-based molecular dynamics simulations, Monte-Carlo, numerical solution of Ginzburg-Landau like continuum dynamical models and Stokes equations, etc. Simulation results are analyzed by using finite-size scaling concepts and simple theoretical arguments.
A brief description is presented below.
1. Optically heated active colloids:
In the last decade, inspired by biological molecular motors, scientists tried to construct artificial devices that can deliver mechanical work or propel themselves in a liquid environment. One approach is to use phoretic transport mechanisms. An interesting candidate for self-propellers is
light-activated colloidal particles that are being used extensively of late. Micron-sized Janus particles, chemically functionalized appropriately in order to give rise to different surface adsorption properties and suspended in a near-critical solvent, undergo active motion when illuminated with a laser of sufficient intensity. Motility of these active particles depends on the non-equilibrium dynamics surrounding the particle which leads to coupled inhomogeneous temperature and concentration fields. This rich mechanism is sensitive to a variety of system parameters, viz., wetting properties of the colloids, illumination intensity, the concentration of the background solvent, hydrodynamic effects, confinement, etc.
2. Confined near-critial fluids:
Physical properties of liquids confined in channels of a few nanometers in diameter can differ significantly from their behavior in bulk. In particular, phase transitions can be suppressed or altered in comparison to the bulk counterpart. Upon approaching the critical point of a continuous phase transition, the order parameter (OP) of fluids near a solid wall deviates in normal direction from its bulk value on the scale of the diverging bulk correlation length. The kind of thermodynamic singularities occuring in this surface layer depends on the boundary conditions for the OP such that each bulk universality class splits up into various surface universality classes. Generically, fluids belong to the so-called normal surface universality class which is characterized by the presence of a symmetry breaking surface field which induces order at the surface even if the bulk is in the disordered phase. Using GPU-based molecular dynamics simulations, we study various dynamical properties of such systems.
3. Collective dynamics in fluids:
With the help of GPU-acclerated molecular dynamics simulations, we study the collective transport properties of binary liquid mixtures near the relevant demixing transition. Associated critical anomalies are quantified with the help of finite-size scaling analysis.
4. Phase separation and aging:
When an initially homogeneous system is quenched inside the binodal, the system phase separates into particle-rich and particle-poor domains. The kinetics of this non-equilibrium process is studied for the elongated percolating morphology as well as for droplet nucleation. In particular, universality of the growth exponent of average domain size is characterized in connection with the underlying growth mechanism. We also study the aging behavior of the fluid which is characterized by the two-time correlation functions of the order parameter.
5. Droplet coalescence:
When two liquid droplets come in contact with each other they form a liquid bridge and the composite structure finally relaxes to a single big drop —a kinetic process known as coalescence. One key aspect of coalescence is the so-called coalescence preference: the product drop (bubble) which emerges from the coalescence of two different-sized parent droplets (bubbles) tends to be placed closer to its larger parent. Spatial and temporal properties of this is studied for droplets and bubbles.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems